A non-linear logistic model describing the diameter kinetics of 'Braeburn' apples, as a function of time from full bloom. - Garriz, Patricia Isabel (2015)
‘Braeburn’ apples (Malus ×domestica Borkh.) are grown throughout the warm regions of the world. They are bi-colored, crisp and very juicy; they store well and withstand the handling demands of international supply chains. The objective of this work was to develop a model to predict the seasonal growth for ‘Braeburn’ apples, expressed in terms of fruit diameter as a function of time from full bloom. Fruit growth was followed at the Experimental Farm of the Universidad Nacional del Comahue, High Valley region, Río Negro, Argentina (38°56’S, 67°59’W), located in an arid region with average annual rainfall of 250 mm, on a sandy loam soil. The study was conducted on ‘Braeburn’ apple trees trained to palmette leaders. The trees were spaced 4.0×2.3 m and row orientation was north-south. Trees were surface irrigated at weekly intervals to match the crop evapotranspiration requirements throughout the season. Five trees were selected at random and four fruits were sampled every two weeks till commercial harvest, during the 2005-06, 2006-07, 2007-08, 2008-09 and 2010-11 growing seasons. The range of sampling dates was 24 and 167 days after full bloom (DFB). Equations were developed with SYSTAT procedure. The R2 values and residual mean squares were used to evaluate the goodness-of-fit of the models. Results showed that the following logistic model provided the most satisfactory fit to the pooled data (n=1088), as compared to the power and linear equations: FD (mm) = 78.00/(1+e1.5355-0.0258 DFB), R2=0.90, P<0.001. This model describes the fruit diameter obtainable in the specific orchard conditions for ‘Braeburn’ apple growth. Fruit maximal absolute growth rate derived from the selected function was 0.50 mm·day-1. A prediction chart was based on the development of the equation and showed ‘Braeburn’ apple sizes at various times after 167 DFB, with practical application to aid crop marketing.